BI Analysis Team Lead

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Requirements:

• 6+ years working experience within Data Analytics or Business Intelligence, driving Analytics/BI projects to successful completion, resulting in business impact.
• 3+ years leading a team of BI/Data & Analytics specialists.
• Strong stakeholder engagement skills to gather and effectively communicate Analytics/BI project requirements, outcomes, results, and status.
• Strong communication and presentations skills able to appropriately structure communication to fit the type of audience i.e. technical vs. non-technical and organizational level (e.g., executive vs. operational manager)
• Strong report/dashboard development and data visualization skills with modern BI tools (e.g., Power BI)
• Extensive experience building semantic models for enterprise-wide reporting.
• Strong Data Modelling expertise (e.g., dimensional Kimball)
• Advanced SQL skills (development and optimization)
• Advanced Excel skills
• R or Python programming for data analytics (desirable)
• Be commercially curious with the ability to understand a business area and its strategic outcomes, as well as the business processes and metrics/levers that drive its performance.
• Knowledge of data analysis techniques, such as time series analysis, scenario analysis, clustering & segmentation, regression, decision trees, forecasting, and interpretation & creation of probability distributions (proficiency in a few of these will suffice)

Responsibilities:

• Partner with stakeholders across all levels and business areas to take-on and propose data-driven solutions to aid the execution and fulfilment of their business strategy.
• Lead and manage a team of Analytics specialists to ensure the delivery of accurate and scalable data & analytics solutions and insights to support business objectives.
• Elicit business requirements and translate them into the appropriate data modelling, reporting and analysis specifications, employing critical thinking to ensure alignment with the actual business need.
• Take ownership of all projects allocated to you, create & maintain the corresponding project roadmap, and proactively communicate the status (including blockers, risks, issues) of the project with all affected stakeholders.
• Share data and analysis results visualized in a manner that is intuitive to the audience and improves access and visibility into the data.
• Train and support the user community in the use of reports, BI tools, and the interpretation of analysis results.
• Provide your team with clear performance standards, hold them accountable, and identify and implement practices to improve team morale and performance.
• Proactively identify and resolve issues or bottlenecks that may impair your team’s ability to meet delivery goals.
• Monitor staff compliance to HR policies and procedures and take corrective action or escalation where needed.
• Help define and improve upon our data warehousing, data governance, and analytics standards & practices through knowledge sharing, internal collaboration, conducting peer reviews, mentorship, and contribution to internal documentation.
• Actively develop and deliver Data & Analytics solutions as part of the team, which will include (not exhaustive): Profile and validate all data intended for use in reporting or analytics to ensure high data quality (business relevance, accuracy, completeness, consistency, timeliness)
• Design, build, deploy, and maintain data models that are optimized for high performance, scale, reusability, ease of maintainability and auditability.
• Design, build, deploy, and maintain reporting semantic layers (on-top of said data models) and reports structured and documented in a manner that enables and facilitates end user self-service access and use of the data.
• Perform data analysis to extract key insights and observations to influence and/or support business decisions and actions.
• Incorporate DevOps practices in all data model and report development; includes but not limited to version control, data quality validation/testing and automated integration and deployment.
• Continuously upskill and stay abreast of new developments in the Data Analytics and Modelling space (tooling, methodologies, applications) to refine the team’s Data Analytics capabilities.
• Perform duties listed above using, but not limited to, the skills and experience outlined in the key requirements section below.